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肝细胞癌的综合组学全景揭示了精准治疗的蛋白质组亚型。

Integrated omics landscape of hepatocellular carcinoma suggests proteomic subtypes for precision therapy.

机构信息

The United Innovation of Mengchao Hepatobiliary Technology Key Laboratory of Fujian Province, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou 350025, China.

Department of Hepatobiliary and Pancreatic Surgery, The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310003, China.

出版信息

Cell Rep Med. 2023 Dec 19;4(12):101315. doi: 10.1016/j.xcrm.2023.101315. Epub 2023 Dec 12.

DOI:10.1016/j.xcrm.2023.101315
PMID:38091986
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC10783603/
Abstract

Patients with hepatocellular carcinoma (HCC) at the same clinical stage can have extremely different prognoses, and molecular subtyping provides an opportunity for individualized precision treatment. In this study, genomic, transcriptomic, proteomic, and phosphoproteomic profiling of primary tumor tissues and paired para-tumor tissues from HCC patients (N = 160) are integrated. Proteomic profiling identifies three HCC subtypes with different clinical prognosis, which are validated in three publicly available external validation sets. A simplified panel of nine proteins associated with metabolic reprogramming is further identified as a potential subtype-specific biomarker for clinical application. Multi-omics analysis further reveals that three proteomic subtypes have significant differences in genetic alterations, microenvironment dysregulation, kinase-substrate regulatory networks, and therapeutic responses. Patient-derived cell-based drug tests (N = 26) show personalized responses for sorafenib in three proteomic subtypes, which can be predicted by a machine-learning response prediction model. Overall, this study provides a valuable resource for better understanding of HCC subtypes for precision clinical therapy.

摘要

肝细胞癌(HCC)患者处于相同临床分期时可能具有截然不同的预后,而分子亚型分类为个体化精准治疗提供了机会。本研究整合了 HCC 患者(N=160)的原发肿瘤组织和配对癌旁组织的基因组、转录组、蛋白质组和磷酸化蛋白质组学分析。蛋白质组学分析确定了三种具有不同临床预后的 HCC 亚型,并在三个公开的外部验证集中得到验证。进一步鉴定出与代谢重编程相关的简化 panel 中的 9 种蛋白,作为一种有潜力的潜在亚型特异性生物标志物,可用于临床应用。多组学分析进一步表明,三种蛋白质组亚型在遗传改变、微环境失调、激酶-底物调控网络和治疗反应方面存在显著差异。基于患者来源的细胞的药物测试(N=26)显示,索拉非尼在三种蛋白质组亚型中的治疗反应存在个体差异,可通过机器学习的反应预测模型进行预测。总的来说,本研究为更好地理解 HCC 亚型以实现精准临床治疗提供了有价值的资源。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9287/10783603/aed73a48e75a/gr7.jpg
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https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9287/10783603/29f5437c5bb2/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9287/10783603/a78a2f00836b/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9287/10783603/72ec5c07a01b/gr3.jpg
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